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Phenotype clusters identified among elderly patients with asthma

Four elderly asthma phenotypic clusters associated with the risk for future acute asthma exacerbation were defined in a recent study.

Researchers performed a k-means nonhierarchical cluster analysis of 872 elderly patients (mean age, 75.1 years; 47.2% men) with asthma from nine centers in South Korea. Clinical cluster trajectories were evaluated through acute asthma exacerbation data collected during a prospective 2-year follow-up. The researchers developed “a decision-tree algorithm” for classification implementation.

“Four clusters of elderly patients were identified: (1) long symptom duration and marked airway obstruction [HR=1], (2) female dominance and normal lung function [HR=0.428; 1 vs. 2, P=.002], (3) smoking male dominance and reduced lung function [HR=0.725; 1 vs. 3, P=.2], and (4) high BMI and borderline lung function [HR=0.58; 1 vs. 4, P=.02],” the researchers wrote.

Time to first acute asthma exacerbation was strongly predicted by cluster grouping (P=.01). Percentage of predicted forced expiratory volume in 1 second and smoking pack-years were two variables included in the decision-tree algorithm. A secondary cohort of 429 elderly patients with asthma (mean age, 70.2 years; 51.3% men) was used to confirm the efficiency of the decision-tree algorithm in proper classification.

“We verified four discrete phenotype clusters of elderly asthmatic patients, which were associated with prospective risk stratification in terms of acute asthma exacerbation,” the researchers concluded. “Our simplified decision-tree algorithm can be easily administered in practice to better understand elderly asthma and to identify an exacerbation-prone subgroup of elderly patients with asthma.”

Disclosure: The researchers report no relevant financial disclosures.